ArticleBiomedicines2022
Point-of-Care Wound Blotting with Alcian Blue Grading versus Fluorescence Imaging for Biofilm Detection and Predicting 90-Day Healing Outcomes.
Article in Biomedicines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.
- The Clinical Utility of Autofluorescence Imaging for Bacterial Detection in Wounds: A Systematic Review.International wound journal · 2025Pooled it
- Article
- Inorganic materials to prevent liquefactive necrosis and improve wound healing: A role of infection control across ischemic models.Materials today. Bio · 2026Article
- Infection-driven proliferative phase impairment in chronic wounds: a mechanistic framework for precision regenerative therapy.Frontiers in immunology · 2026Review
- Clinical and Economic Evidence Supporting the Value of Fluorescence Imaging of Bacteria in Wound Care.Journal of market access & health policy · 2025Review
- Clinical Effectiveness of Monofilament Fibre Pads for Bacterial and Biofilm Removal in Pressure Injuries: A Retrospective Cohort Study.Wound repair and regeneration : official publication of the Wound Healing Society [and] the European Tissue Repair SocietyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
Biofilm infection has been identified as a crucial factor of the pathogenesis of chronic wound, but wound biofilm diagnosis remains as an unmet clinical need. We previously proposed a modified wound blotting technique using Alcian blue staining for biofilm detection that was characterized as being non-invasive, time-saving, non-expansive, and informative for biofilm distribution. In this study, we adapted a novel Alcian blue grading method as the severity of biofilm infection for the wound blotting technique and compared its biofilm detection efficacy with MolecuLight i:X- a point-of-care florescence imaging device to detect bacteria and biofilm in wounds. Moreover, their predictive value of complete wound healing at 90 days was analyzed. When validated with wound culture results in the 53 enrolled subjects with chronic wounds, the modified wound blotting method showed a strong association with wound culture, while MolecuLight i:X only exhibited a weak association. In predicting 90-day wound outcomes, the modified wound blotting method showed a strong association (Kendall’s tau value = 0.563, p < 0.001), and the wound culture showed a moderate association (Spearman’s rho = 0.535, p < 0.001), but MolecuLight i:X exhibited no significant association (p = 0.184). In this study, modified wound blotting with the Alcian blue grading method showed superior value to MolecuLight i:X both in biofilm detection and predictive validity in 90-day wound-healing outcomes.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.